Microcontroller Based Water Measurement Level Prototype Using Fuzzy Logic Method

Dalle, Juhriyansyah; Elfirman, M. Ziki; Sufyan, Muhammad

doi:10.18421/tem92-36

Cited by 4 publications

(3 citation statements)

References 26 publications

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“…Some of the physical data obtained by the sensor are raw data that must be processed and analyzed further by the processor, i.e., a microcontroller [42], [43]. However, to display data processed by the processor using the LCD display [44], while Ruobing [45] used the display on a computer or smartphone. Reporting using this device can make it easier for users, i.e., vessel engine operators, maintenance technicians, and vessel owners.…”

Section: Qs2 (The Parts Used As a Monitoring Device For Fishing Vessel Propulsion Engines)mentioning

confidence: 99%

Modern Monitoring Instrument to Support Fishing Vessel Operation and Maintenance: A Review

Abrori¹,

Sidhi²,

Prasetyo³

2021

International Journal on Advanced Science, Engineering and Information Technology

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Determining the maintenance strategy for fishing vessels propulsion engines can use engine operational monitoring data. This data is used to prepare the implementation time, spare parts, labor, and costs. Unfortunately, many fishing vessels do not have this data. Currently, electronic devices are available for monitoring machine operations. This device is cheap, easy to use, takes responsibility for various physical quantity parameters, displays it on LCD, stores it digitally, and transmits data wirelessly. This paper aims to review the application of engine operational monitoring tools to apply to fishing vessel propulsion engines. The material used is scientific articles consisting of journals and proceedings indexed by online databases. Several keywords are used to obtain scientific articles that are suitable for the study. The method used is a literature review that is systematically reviewed by applying inclusion and exclusion. The results obtained in this article are the parameters for monitoring propulsion engines, namely temperature, pressure, rotational speed, and hours the engine runs. The monitoring device requires sensors to detect physical parameters, a microcontroller to process data, an LCD to display monitoring results, and memory to store data to obtain this data. The device supports wireless communication via Bluetooth or WiFi radio signal. Fishing vessels are operating in offshore areas that are not covered by internet networks as IoT communication transmissions. Further research on how to transmit operational engine data from offshore to onshore without an internet signal so that data can be accessed using the internet network.

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Section: Qs2 (The Parts Used As a Monitoring Device For Fishing Vessel Propulsion Engines)mentioning

confidence: 99%

Modern Monitoring Instrument to Support Fishing Vessel Operation and Maintenance: A Review

Abrori¹,

Sidhi²,

Prasetyo³

2021

International Journal on Advanced Science, Engineering and Information Technology

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“…Monitoring pipelines that transport hazardous products can be made more efficient through the use of early warning signatures and environmental monitoring [12], [13]. The potential applications of monitoring systems have been discussed in the scientific literature.…”

Section: Introductionmentioning

confidence: 99%

IoT-Based Detection and Early Warning System for Acid Leaking in Underground Pipeline

Hairuddin¹,

Nazri²,

Saaid³

2022

TEM Journal

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Leaks in pipelines caused by acid are destructive to both economic growth and capital which should be avoided at all costs. Damage to underground pipelines is caused by a hard-to-find leak, the unavailability of a real-time monitoring system and the lack of a pipeline history database. The aim of this work is to develop an early warning system to detect acid leaking in the pipeline using Internet of Things (IoT) technology. To detect changes in the pH of acid soil parameters near the pipeline, two mechanisms are required: first, to provide an early warning before the leak is detected and second, to report the occurrence of the leak. The notification system is equipped with three LED indicators, each showing the offline, online and signal detection status. The novelty of the work is a prototype that can detect the acid leak in the pipeline and record the pH values in a database for future research. Using continuous pH monitoring, real-time analysis and a database, this system can detect leaks before they become a major problem. Consequently, the manufacturing industry will benefit from this initiative as it is automated, efficient and cost-effective.

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“…Meanwhile, this paper examined DC motors (not brushless DC motors) using FLC and controlled the output using adaptive LMS (Hybrid FLC and adaptive LMS). The study that used Fuzzy Logic Method to develop prototype for reading the turbidity level of water and sent a real-time report was done, but that did not calculate the volume [8].…”

Section: Introductionmentioning

confidence: 99%

Hybrid FLC-LMS Algorithm for Predicting Sediment Volume in the River

Prasetyowati¹

2021

IJIES

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Problems such as flooding, various diseases from microbial pathogens, rivers becoming slum and unsightly, reduced availability: The data found that 82% of the 550 rivers in Indonesia were polluted and in critical condition. The high level of pollution caused various of clean water and many more. Sediment was one of the causes of that problem. There have been many studies detecting objects in the water, but no one predicted the volume of objects in the water. The purpose of this research is to make a device to detect the volume of sediment in the rivers to improve the performance of river monitoring. A device was equipped with an infrared sensor. Raising and lowering the sensor under the device was controlled by the front DC motor with a Fuzzy Logic Controller (FLC) algorithm using two input and one output. Error (E) and change of error (CE) were inputs for FLC and change of control was the output. The fuzzy membership function depended on the distance of the sensor to the sediment. The number of membership functions used was less than the previous research, so the calculation was much simple. This research used hybrid FLC and Adaptive LMS predictive algorithm. Fuzzy Logic Controller was for controlling the Front DC motor when raising and lowering the sensor and Adaptive LMS predictive algorithm was for predicting the volume and minimalizing the error calculation. PID control was also used as a comparison. The results showed that using the FLC algorithm can find sediment in less than four seconds with an error rate of 0.0005, while the PID sensor found sediment in more than 4 seconds with an error rate of 0.001. In addition, the Adaptive LMS predictive algorithm minimized the error calculation with an accuracy level of 99.66 percent.

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Microcontroller Based Water Measurement Level Prototype Using Fuzzy Logic Method

Cited by 4 publications

References 26 publications

Modern Monitoring Instrument to Support Fishing Vessel Operation and Maintenance: A Review

Modern Monitoring Instrument to Support Fishing Vessel Operation and Maintenance: A Review

IoT-Based Detection and Early Warning System for Acid Leaking in Underground Pipeline

Hybrid FLC-LMS Algorithm for Predicting Sediment Volume in the River

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